Papers
6
Total Citations
37
H-Index
4
About
Andrew Yee is an emerging researcher at the forefront of surgical data science, with a focused expertise in robotic surgery performance assessment and surgical education. His work centers on developing and validating objective performance indicators (OPIs) — quantitative, intraoperative metrics derived from robotic surgical systems that can meaningfully evaluate surgeon skill and technical execution. Through a series of influential pilot and cohort studies, Yee has demonstrated that kinematic data can reliably distinguish experienced surgeons from trainees across diverse procedures, including robotic inguinal hernia repair, cholecystectomy, and Roux-en-Y gastric bypass. A particularly notable contribution is his introduction of "active control time" as a measurable proxy for trainee participation, offering surgical educators a practical tool for tracking hands-on engagement. His 2024 systematic review, his most-cited work with 10 citations, synthesized the broader landscape of OPI research and helped solidify the field's conceptual foundations. Collectively accumulating over 37 citations within just a few years, Yee's scholarship is shaping how surgical training is standardized, assessed, and ultimately improved — with meaningful implications for both patient safety and the next generation of surgeons.
Research Focus
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Top Papers
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